Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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Acoustic emission-based process monitoring in the milling of carbon fibre-reinforced plastics

2022 , Uhlmann, E. , Holznagel, Tobias

Milling of fibre-reinforced plastics is a challenging task. The highly abrasive fibres lead to high tool wear and coating failures, which cause increasing process forces and temperatures. Machining with a worn tool, in turn, can result in unwanted workpiece damages such as delamination or fibre protrusion. Reliable monitoring of the process must therefore be able to detect damages to the milling tool and the workpiece alike. The presented process monitoring approach measures the acoustic emission generated by the milling tool cutting edge entering the workpiece with a sensor attached to the tool holder. Specific acoustic emission frequency spectra and waveforms are emitted in the cutting zone for different tool wear states. Coating failures as well as other acoustic emission events due to workpiece damages can be robustly detected and distinguished by feature extraction and signal processing as well. The developed setup, the monitoring parameterisation techniques and signal processing algorithms as well as experimental and monitoring results are presented and discussed in this paper.

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Practical Approaches for Acoustic Emission Attenuation Modelling to Enable the Process Monitoring of CFRP Machining

2022 , Uhlmann, Eckart , Holznagel, Tobias , Clemens, Robin

Acoustic emission-based monitoring of the milling process holds the potential to detect undesired damages of fibre-reinforced plastic workpieces, such as delamination or matrix cracking. In addition, abrasive tool wear, tool breakage, or coating failures can be detected. As measurements of the acoustic emission are impacted by attenuation, dispersion, and reflection as it propagates from source to sensor, the waveforms, amplitudes, and frequency content of a wave packet differ depending on the propagation length in the workpiece. Since the distance between acoustic emission sources and a stationary sensor attached to the workpiece changes continually in circumferential milling, the extraction of meaningful information from the raw measurement data is challenging and requires appropriate signal processing and frequency-dependent amplification. In this paper, practical and robust approaches, namely experimentally identified transfer functions and frequency gain parameter tables for attenuation modelling, which in reverse enable the reconstruction of frequency spectra emitted at the acoustic emission source, are presented and discussed. From the results, it is concluded that linear signal processing can largely compensate for the influence of attenuation, dispersion, and reflection on the frequency spectra and can therefore enable acoustic emission based process monitoring.

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